Medical image based breast cancer diagnosis: State of the art and future directions
The intervention of medical imaging has significantly improved early diagnosis of breast
cancer. Different radiological and microscopic imaging modalities are frequently utilized by …
cancer. Different radiological and microscopic imaging modalities are frequently utilized by …
Evolutionary design of neural network architectures: a review of three decades of research
HT Ünal, F Başçiftçi - Artificial Intelligence Review, 2022 - Springer
We present a comprehensive review of the evolutionary design of neural network
architectures. This work is motivated by the fact that the success of an Artificial Neural …
architectures. This work is motivated by the fact that the success of an Artificial Neural …
Diagnosis of breast cancer using machine learning techniques-a survey
Breast cancer is a disease in which the cells of the breast develop unnaturally and
uncontrollably, resulting in a mass called a tumor. If lumps in the breast are not addressed …
uncontrollably, resulting in a mass called a tumor. If lumps in the breast are not addressed …
Recent advancements in machine learning and deep learning-based breast cancer detection using mammograms
Objective: Mammogram-based automatic breast cancer detection has a primary role in
accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is …
accurate cancer diagnosis and treatment planning to save valuable lives. Mammography is …
Breast cancer detection in thermography using convolutional neural networks (cnns) with deep attention mechanisms
A Alshehri, D AlSaeed - Applied Sciences, 2022 - mdpi.com
Featured Application Medical diagnosis and computer-aided diagnosis systems. Abstract
Breast cancer is one of the most common types of cancer among women. Accurate …
Breast cancer is one of the most common types of cancer among women. Accurate …
Breast cancer diagnosis in thermography using pre-trained vgg16 with deep attention mechanisms
A Alshehri, D AlSaeed - Symmetry, 2023 - mdpi.com
One of the most prevalent cancers in women is breast cancer. The mortality rate related to
this disease can be decreased by early, accurate diagnosis to increase the chance of …
this disease can be decreased by early, accurate diagnosis to increase the chance of …
Breast cancer patient characterisation and visualisation using deep learning and fisher information networks
Breast cancer is the most commonly diagnosed female malignancy globally, with better
survival rates if diagnosed early. Mammography is the gold standard in screening …
survival rates if diagnosed early. Mammography is the gold standard in screening …
Breast Mammograms Diagnosis Using Deep Learning: State of Art Tutorial Review
Usually, screening (mostly mammography) is used by radiologists to manually detect breast
cancer. The likelihood of identifying suspected cases as false positives or false negatives is …
cancer. The likelihood of identifying suspected cases as false positives or false negatives is …
Fine-tuning pre-trained networks with emphasis on image segmentation: A multi-network approach for enhanced breast cancer detection
Accurate classification of mammography images into normal and cancerous categories is
critical for the early detection of breast cancer. This study utilizes transfer learning and deep …
critical for the early detection of breast cancer. This study utilizes transfer learning and deep …
Towards non-data-hungry and fully-automated diagnosis of breast cancer from mammographic images
H Ghazouani, W Barhoumi - Computers in Biology and Medicine, 2021 - Elsevier
Analysing local texture and generating features are two key issues for automatic cancer
detection in mammographic images. Recent researches have shown that deep neural …
detection in mammographic images. Recent researches have shown that deep neural …